The errors, insights and lessons of famous AI predictions – and what they mean for the future

Armstrong, Stuart; Sotala, Kaj; hÉigeartaigh, Seán Ó

doi:10.1080/0952813x.2014.895105

Cited by 49 publications

(37 citation statements)

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“…One striking illustration of this, shown in Fig. 1, comes from a compilation of AI experts' published predictions for when a high-level AI would be achieved (Armstrong, Sotala, & O h Eigeartaigh, 2014). For example, in 1988, Hans Moravec predicted human-like levels of intelligence in robots in the Year 2028.…”

Section: Beyond the Corementioning

confidence: 99%

“…Where the best-fitting line for the set of forecasts intersects the line Y = X provides a prediction (the year 2026) for when the telescope will actually be launched. By contrast, expert predictions for when a high-level Artificial Intelligence will be built, assembled by Armstrong, Sotala, and O h Eigeartaigh (2014), are plotted in panel (B) with a best fitting blue line that has a slope >1, meaning that it never intersects with the red Y = X line in the future. explorations into creating working models of minds show promise, but we are also in need of fundamentally transformative approaches.…”

Section: Beyond the Corementioning

confidence: 99%

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Becoming Cognitive Science

Goldstone

2019

Topics in Cognitive Science

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Cognitive science continues to make a compelling case for having a coherent, unique, and fundamental subject of inquiry: What is the nature of minds, where do they come from, and how do they work? Central to this inquiry is the notion of agents that have goals, one of which is their own persistence, who use dynamically constructed knowledge to act in the world to achieve those goals. An agentive perspective explains why a special class of systems have a cluster of co‐occurring capacities that enable them to exhibit adaptive behavior in a complex environment: perception, attention, memory, representation, planning, and communication. As an intellectual endeavor, cognitive science may not have achieved a hard core of uncontested assumptions that Lakatos (1978) identifies as emblematic of a successful research program, but there are alternative conceptions according to which cognitive science has been successful. First, challenges of the early, core tenet of “Mind as Computation” have helped put cognitive science on a stronger foundation—one that incorporates relations between minds and their environments. Second, even if a full cross‐disciplinary theoretic consensus is elusive, cognitive science can inspire distant, deep, and transformative connections between pairs of fields. To be intellectually vital, cognitive science need not resemble a traditional discipline with its associated insularity and unchallenged assumptions. Instead, there is strength and resilience in the diverse perspectives and methods that cognitive science assembles together. This interdisciplinary enterprise is fragile and perhaps inherently unstable, as the looming absorption of cognitive science into psychology shows. Still, for many researchers, the excitement and benefits of triangulating on the nature of minds by integrating diverse cases cannot be secured by a stable discipline with an uncontested core of assumptions.

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Section: Beyond the Corementioning

confidence: 99%

Section: Beyond the Corementioning

confidence: 99%

Becoming Cognitive Science

Goldstone

2019

Topics in Cognitive Science

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“…So, we decided to ask the experts what they predict the future holds -knowing that predictions on the future of AI are often not too accurate (see Armstrong, Sotala, & O Heigeartaigh, 2014) and tend to cluster around 'in 25 years or so', no matter at what point in time one asks. 1…”

Section: Introductionmentioning

confidence: 99%

Future Progress in Artificial Intelligence: A Survey of Expert Opinion

2016

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There is, in some quarters, concern about high-level machine intelligence and superintelligent AI coming up in a few decades, bringing with it significant risks for humanity. In other quarters, these issues are ignored or considered science fiction. We wanted to clarify what the distribution of opinions actually is, what probability the best experts currently assign to high-level machine intelligence coming up within a particular time-frame, which risks they see with that development, and how fast they see these developing. We thus designed a brief questionnaire and distributed it to four groups of experts in 2012/2013. The median estimate of respondents was for a one in two chance that highlevel machine intelligence will be developed around 2040-2050, rising to a nine in ten chance by 2075. Experts expect that systems will move on to superintelligence in less than 30 years thereafter. They estimate the chance is about one in three that this development turns out to be 'bad' or 'extremely bad' for humanity.

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“…An Active Learning approach in which the Machine 3 Making predictions about technological progress is also notoriously difficult (Armstrong et al, 2014). 4 The direction of employment change -in both absolute and relative terms -was projected accurately for 70% of detailed occupations included in Handel's evaluation.…”

Section: Uncertainty Samplingmentioning

confidence: 99%

Transforming 21st-century Leader Competencies by Developing Mindfulness

Gąsiorowska¹,

Gąsiorowski

2019

e-mentor

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Questions for the authorsQuestions for the authors can be sent to:hasan.bakhshi@nesta.org.uk (Hasan Bakhshi) jd@robots. ox.ac.uk (Jonathan M. Downing) mosb@robots.ox.ac.uk (Michael A. Osborne) The contents of this paper and the opinions expressed herein are those of the Authors alone.ISBN: 978-0-992-42595-1 ABOUT PEARSONPearson is the world's learning company. We're experts in educational course ware and assessment, and provide teaching and learning services powered by technology. We believe that learning opens up opportunities, creating fulfilling careers and better lives. So it's our mission to help people make progress in their lives through learning. ABOUT NESTANesta is a global innovation foundation. We back new ideas to tackle the big challenges of our time, making use of our knowledge, networks, funding and skills. We work in partnership with others, including governments, businesses and charities. We are a UK charity that works all over the world, supported by a financial endowment.To find out more visit www.nesta.org.uk. ABOUT THE OXFORD MARTIN SCHOOLThe Oxford Martin School at the University of Oxford is a world-leading centre of pioneering research that addresses global challenges. We invest in research that cuts across disciplines to tackle a wide range of issues such as climate change, disease and inequality. We support novel, high risk and multidisciplinary projects that may not fit within conventional funding channels. We do this because breaking boundaries can produce results that could dramatically improve the wellbeing of this and future generations. We seek to make an impact by taking new approaches to global problems, through scientific and intellectual discovery, by developing policy recommendations and working with a wide range of stakeholders to translate them into action. www.oxfordmartin.ox.ac.ukTwitter: @oxmartinschool Facebook: /oxfordmartinschool

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The errors, insights and lessons of famous AI predictions – and what they mean for the future

Cited by 49 publications

References 38 publications

Becoming Cognitive Science

Becoming Cognitive Science

Future Progress in Artificial Intelligence: A Survey of Expert Opinion

Transforming 21st-century Leader Competencies by Developing Mindfulness

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